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Discrete Choice Simulation/Evidence
Method evidence record

Discrete Choice Simulation

Discrete choice simulation is a behavioural modelling method — grounded in random utility theory formalised by Daniel McFadden in the 1970s and extended to simulation-based estimation by Kenneth Train — that estimates how individuals choose among mutually exclusive alternatives and then uses those estimated preference parameters to forecast how choice shares would shift under hypothetical policy or market scenarios. It is the dominant quantitative tool in transport demand analysis, health economics, environmental valuation, and marketing research.

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Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Discrete Choice Simulation (Stated Preference / SP Simulation)
Taxonomic method record · process-pipeline / simulation
  • Train, K.E. (2009). Discrete Choice Methods with Simulation (2nd ed.). Cambridge University Press. · DOI 10.1017/CBO9780511753930
  • Ben-Akiva, M. & Lerman, S.R. (1985). Discrete Choice Analysis: Theory and Application to Travel Demand. MIT Press. · ISBN 978-0262022170
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Curated claims

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Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

See alsoConjoint Analysismachine-suggested · Relational suggestion, not evidence.Same method familyMicrosimulationmachine-suggested · Relational suggestion, not evidence.See alsoMixed Logitmachine-suggested · Relational suggestion, not evidence.See alsoMONTE-CARLO-SIMULATIONmachine-suggested · Relational suggestion, not evidence.See alsoMultinomial Logitmachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

2 recorded citations, copied from the method source record.

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